The trend of change in cervical tumor size and time to death of hospitalized patients in northwestern Ethiopia during 2018-2022: Retrospective study design

Abstract

Background and aims: Cervical cancer is the fourth most common cause of cancer-related death in the world. The objective of this study was to determine factors that affect the longitudinal change of tumor size and the time to death of outpat.

Methods: A retrospective follow-up study was carried out among 322 randomly selected patients with cervical cancer at the University of Gondar Referral Hospital from May 15, 2018 to May 15, 2022. Data were extracted from the patient's chart from all patients' data records. Kaplan-Meier estimator, log-rank test, the Cox proportional-hazard model, and the joint model for the two response variables simultaneously were used.

Results: Among 322 outpatients with cervical cancer, 148 (46%) of them were human immunodeficiency virus (HIV) positive and 107 (33.3%) of them died. The results of joint and separate models show that there is an association between survival and the longitudinal data in the analysis; it indicates that there is a dependency between longitudinal terms of cervical tumor size and time-to-death events. A unit centimeter square rise in tumor size, corresponding to an exp(0.8502) = 2.34 times, significantly raised the mortality risk.

Conclusion: The study showed that HIV, stage of cancer, treatment, weight, history of abortion, oral contraceptive use, smoking status, and visit time were statistically significant factors for the two outcomes jointly.

Implications: As a result, adequate health services and adequate resource allocations are critical for cervical cancer control and prevention programs. Therefore, the government should provide adequate funding and well-trained health professionals to hospitals to sustain screening programs with appropriate coverage of cervical cancer patient treatments.

Keywords: Cox proportional‐hazard model; joint model; time to death; tumor size.

Figure 1

Kaplan–Meier (KM) plot of oral contraceptive use and smoking status of patients, 2018–2022.

Figure 2

Scaled Schoenfeld residual plot for some selected predictor variables, University of Gondar Referral Hospital, 2018–2022.

Figure 3

Diagnostics plot for fitted Joint model of outpatients with cervical cancer, University of Gondar Referral Hospital, 2018–2022.

Figure 4

Diagnostics plot for longitudinal submodel from the joint model, University of Gondar Referral Hospital, 2018–2022.

Figure 5

Diagnostics plot for survival submodel from q joint model, University of Gondar Referral Hospital, 2018–2022.